Functions, mechanisms, and clinical applications of lncRNA LINC00857 in cancer pathogenesis

Developing a prognostic model using machine learning for disulfidptosis related lncRNA in lung adenocarcinoma

Disulfidptosis represents a novel cell death mechanism triggered by disulfide stress, with potential implications for advancements in cancer treatments. Although emerging evidence highlights the critical regulatory roles of long non-coding RNAs (lncRNAs) in the pathobiology of lung adenocarcinoma (LUAD), research into lncRNAs specifically associated with disulfidptosis in LUAD, termed disulfidptosis-related lncRNAs (DRLs), remains insufficiently explored. Using The Cancer Genome Atlas (TCGA)-LUAD dataset, we implemented ten machine learning techniques, resulting in 101 distinct model configurations. To assess the predictive accuracy of our model, we employed both the concordance index (C-index) and receiver operating characteristic (ROC) curve analyses. For a deeper understanding of the underlying biological pathways, we referred to the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) for functional enrichment analysis. Moreover, we explored differences in the tumor microenvironment between high-risk and low-risk patient cohorts. Additionally, we thoroughly assessed the prognostic value of the DRLs signatures in predicting treatment outcomes. The Kaplan-Meier (KM) survival analysis demonstrated a significant difference in overall survival (OS) between the high-risk and low-risk cohorts (p < 0.001). The prognostic model showed robust performance, with an area under the ROC curve exceeding 0.75 at one year and maintaining a value above 0.72 in the two and three-year follow-ups. Further research identified variations in tumor mutational burden (TMB) and differential responses to immunotherapies and chemotherapies. Our validation, using three GEO datasets (GSE31210, GSE30219, and GSE50081), revealed that the C-index exceeded 0.67 for GSE31210 and GSE30219. Significant differences in disease-free survival (DFS) and OS were observed across all validation cohorts among different risk groups. The prognostic model offers potential as a molecular biomarker for LUAD prognosis.

Deciphering the oncogenic landscape: Unveiling the molecular machinery and clinical significance of LncRNA TMPO-AS1 in human cancers

The in-depth exploration of long non-coding RNAs (lncRNAs) reveals their pivotal and diverse roles in various disorders, particularly cancer. Within this intricate landscape, thymopoietin-antisense RNA-1 (TMPO-AS1) emerges as a noteworthy instigator of oncogenesis in humans. This exhaustive review seeks to intricately unravel the present understanding of TMPO-AS1, emphasizing its molecular foundations and highlighting its clinical applications in the realm of cancer research. TMPO-AS1 consistently exhibits heightened expression across a spectrum of cancer types, encompassing lung, colorectal, breast, cervical, bladder, pancreatic, hepatocellular, gastric, ovarian, and osteosarcoma. Elevated levels of TMPO-AS1 are intricately linked to unfavorable prognoses, accompanied by distinctive clinical and pathological characteristics. Functionally, TMPO-AS1 showcases its prowess in enhancing cancer cell migration, invasion, proliferation, and orchestrating epithelial-mesenchymal transition (EMT) through a myriad of molecular mechanisms. These mechanisms entail intricate interactions with proteins, microRNAs, and intricate signaling pathways. Furthermore, TMPO-AS1 is intricately involved in regulating critical cellular processes, including apoptosis and the cell cycle. The mounting evidence converges towards the potential of TMPO-AS1 serving as a diagnostic and prognostic biomarker, further entwined with its potential role in influencing chemoresistance in cancer. This potential is underscored by its consistent associations with clinical outcomes and treatment responses. This comprehensive investigation not only consolidates our existing knowledge of TMPO-AS1's multifaceted roles but also sheds illuminating insights on its profound significance in the intricate landscape of cancer biology, paving the way for potential applications in clinical practice.

LncRNA PRBC induces autophagy to promote breast cancer progression through modulating PABPC1-mediated mRNA stabilization

Breast cancer is one of the major malignant tumors among women worldwide. Long noncoding RNAs (lncRNAs) have been documented as significant modulators in the development and progression of various cancers; however, the contribution of lncRNAs to breast cancer remains largely unknown. In this study, we found a novel lncRNA (NONHSAT137675) whose expression was significantly increased in the breast cancer tissues. We named the novel lncRNA as lncRNA PRBC (PABPC1-related lncRNA in breast cancer) and identified it as a key lncRNA associated with breast cancer progression and prognosis. Functional analysis displayed that lncRNA PRBC could promote autophagy and progression of breast cancer. Mechanistically, we verified that lncRNA PRBC physically interacted with PABPC1 through RIP assay, and PABPC1 overexpression could reverse the inhibiting effect of lncRNA PRBC knockdown on the malignant behaviors in breast cancer cells. Knockdown of lncRNA PRBC interfered the translocation of PABPC1 from nucleus to cytoplasm as indicated by western blot and IF assays. Significantly, the cytoplasmic location of PABPC1 was required for the interaction between PABPC1 and AGO2, which could be enhanced by lncRNA PRBC overexpression, leading to strengthened recruitment of mRNA to RNA-induced silencing complex (RISC) and thus reinforcing the inhibition efficiency of miRNAs. In general, lncRNA PRBC played a critical role in malignant progression of breast cancer by inducing the cytoplasmic translocation of PABPC1 to further regulate the function of downstream miRNAs. This study provides novel insight on the molecular mechanism of breast cancer progression, and lncRNA PRBC might be a promising therapeutic target and prognostic predictor for breast cancer.